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» Mining top-K frequent itemsets from data streams
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KDD
2008
ACM
217views Data Mining» more  KDD 2008»
14 years 9 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
DASFAA
2008
IEEE
149views Database» more  DASFAA 2008»
13 years 9 months ago
A Test Paradigm for Detecting Changes in Transactional Data Streams
A pattern is considered useful if it can be used to help a person to achieve his goal. Mining data streams for useful patterns is important in many applications. However, data stre...
Willie Ng, Manoranjan Dash
SDM
2011
SIAM
242views Data Mining» more  SDM 2011»
12 years 11 months ago
Fast Algorithms for Finding Extremal Sets
Identifying the extremal (minimal and maximal) sets from a collection of sets is an important subproblem in the areas of data-mining and satisfiability checking. For example, ext...
Roberto J. Bayardo, Biswanath Panda
ICDM
2002
IEEE
114views Data Mining» more  ICDM 2002»
14 years 1 months ago
Online Algorithms for Mining Semi-structured Data Stream
In this paper, we study an online data mining problem from streams of semi-structured data such as XML data. Modeling semi-structured data and patterns as labeled ordered trees, w...
Tatsuya Asai, Hiroki Arimura, Kenji Abe, Shinji Ka...
MLDM
2007
Springer
14 years 2 months ago
Mining Frequent Trajectories of Moving Objects for Location Prediction
Advances in wireless and mobile technology flood us with amounts of moving object data that preclude all means of manual data processing. The volume of data gathered from position...
Mikolaj Morzy